Our trained model parameters are available at github.com/dsjamieson/map2map_emu. We train and test the neural networks with map2map (github.com/eelregit/map2map). map2map is a neural network framework for field-to-field emulators, based on PyTorch[1]}. It implements the aforementioned mechanisms to fully preserve translational symmetry including the boundary conditions, and to do rotational data augmentation, for problems of arbitrary dimensions. It can also optimize the data loading IO at training time, so that the GPUs are not starved of data due to their high performance.
